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arXiv 2023年

作者： Li, Yuzhu Pillar, Nir Li, Jingxi Liu, Tairan Wu, Di Sun, Songyu Ma, Guangdong de Haan, Kevin Huang, Luzhe Hamidi, Sepehr Urisman, Anatoly Haran, Tal Keidar Dean Wallace, William Zuckerman, Jonathan E. Ozcan, Aydogan Electrical and Computer Engineering Department University of California Los AngelesCA90095 United States Bioengineering Department University of California Los Angeles90095 United States University of California Los AngelesCA90095 United States Computer Science Department University of California Los AngelesCA90095 United States School of Physics Xi'an Jiaotong University Shaanxi Xi’an710049 China Department of Pathology and Laboratory Medicine David Geffen School of Medicine University of California Los AngelesCA90095 United States Department of Pathology University of California San FranciscoCA94143 United States Department of Pathology Hadassah Hebrew University Medical Center Jerusalem91120 Israel Department of Pathology Keck School of Medicine University of Southern California Los AngelesCA90033 United States Department of Surgery University of California Los AngelesCA90095 United States

Histological examination is a crucial step in an autopsy;however, the traditional histochemical staining of postmortem samples faces multiple challenges, including the inferior staining quality due to autolysis caused by delayed fixation of cadaver tissue, as well as the resource-intensive nature of chemical staining procedures covering large tissue areas, which demand substantial labor, cost, and time. These challenges can become more pronounced during global health crises when the availability of histopathology services is limited, resulting in further delays in tissue fixation and more severe staining artifacts. Here, we report the first demonstration of virtual staining of autopsy tissue and show that a trained neural network can rapidly transform autofluorescence images of label-free autopsy tissue sections into brightfield equivalent images that match hematoxylin and eosin (H&E) stained versions of the same samples, eliminating autolysis-induced severe staining artifacts inherent in traditional histochemical staining of autopsied tissue. Our virtual H&E model was trained using >0.7 TB of image data and a data-efficient collaboration scheme that integrates the virtual staining network with an image registration network. The trained model effectively accentuated nuclear, cytoplasmic and extracellular features in new autopsy tissue samples that experienced severe autolysis, such as COVID-19 samples never seen before, where the traditional histochemical staining failed to provide consistent staining quality. This virtual autopsy staining technique can also be extended to necrotic tissue, and can rapidly and cost-effectively generate artifact-free H&E stains despite severe autolysis and cell death, also reducing labor, cost and infrastructure requirements associated with the standard histochemical staining. Copyright © 2023, The Authors. All rights reserved.

关键词： Tissue

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Photonic Crystal Enhanced Fluorescence with DNA-based Nano-gripper for Ultrasensitive SARS-CoV-2 Biosensing

Photonic Crystal Enhanced Fluorescence with DNA-based Nano-g...

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IEEE Photonics Conference (IPC)

作者： Yanyu Xiong Lifeng Zhou Laura Cooper Skye Shepherd Tingjie Song Abhisek Dwivedy Lijun Rong Tong Wang Xing Wang Brian T. Cunningham Department of Electrical and Computer Engineering Holonyak Micro and Nanotechnology Laboratory University of Illinois at Urbana−Champaign Urbana Illinois USA Carl R. Woese Institute for Genomic Biology University of Illinois at Urbana−Champaign Urbana Illinois USA Department of Microbiology and Immunology College of Medicine University of Illinois at Chicago Chicago IL USA Department of Bioengineering University of Illinois at Urbana-Champaign Urbana IL USA Department of Chemistry University of Illinois at Urbana-Champaign Urbana IL USA Advanced Science Research Center at Graduate Center City University of New York New York NY USA Cancer Center at Illinois University of Illinois at Urbana-Champaign Urbana IL USA

DNA-origami based nano-grippers, integrated with aptamer-based nanoswitches, generate fluorescent signals when detecting SARS-CoV-2. The integration of Photonic Crystal Enhanced Fluorescence Microscope enables a 10 4 -fold enhancement compared to a single fluorophore reporter on glass substrate, providing a promising tool for ultrasensitive detection and rapid diagnostics.

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Linewidth broadening induced by fundamental thermal fluctuations in metallo-dielectric nanolasers

Linewidth broadening induced by fundamental thermal fluctuat...

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CLEO: Applications and Technology, CLEO_AT 2020

作者： Jiang, Sizhu Pan, Si Hui Deka, Suruj S. Chengyi-Fang Chen, Zijun Fainman, Yeshaiahu El Amili, Abdelkrim Department of Electrical and Computer Engineering University of California San Diego San DiegoCA92093-0407 United States Department of Physics University of California San Diego San DiegoCA92093-0407 United States Material Science and Engineering Program University of California San Diego San DiegoCA92093-0407 United States

We demonstrate that the fundamental thermal fluctuations can induce significant linewidth broadening effect in metallo-dielectric nanolasers through numerical simulation. Broader linewidths are observed with the decre... 详细信息

ISBN: (数字)9781943580767

ISBN: (纸本)9781557528209

关键词： Linewidth

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Linewidth Broadening Induced by Fundamental Thermal Fluctuations in Metallo-Dielectric Nanolasers

Linewidth Broadening Induced by Fundamental Thermal Fluctuat...

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2020 Conference on Lasers and Electro-Optics, CLEO 2020

作者： Jiang, Sizhu Pan, Si Hui Deka, Suruj S. Chengyi-Fang Chen, Zijun Fainman, Yeshaiahu Amili, Abdelkrim El Department of Electrical and Computer Engineering University of California San Diego San DiegoCA92093-0407 United States Department of Physics University of California San Diego San DiegoCA92093-0407 United States Material Science and Engineering Program University of California San Diego La Jolla CA92093-0407 United States

ISBN: (纸本)9781943580767

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Experimental implementation of an efficient test of quantumness

arXiv

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arXiv 2022年

作者： Lewis, Laura Zhu, Daiwei Gheorghiu, Alexandru Noel, Crystal Katz, Or Harraz, Bahaa Wang, Qingfeng Risinger, Andrew Feng, Lei Biswas, Debopriyo Egan, Laird Vidick, Thomas Cetina, Marko Monroe, Christopher Institute for Quantum Information and Matter Department of Computing and Mathematical Sciences California Institute of Technology CA91125 United States Division of Physics Mathematics and Astronomy California Institute of Technology CA91125 United States Joint Quantum Institute Departments of Physics and Electrical and Computer Engineering University of Maryland College ParkMD20742 United States Joint Center for Quantum Information and Computer Science NIST University of Maryland College ParkMD20742 United States IonQ Inc. College ParkMD20740 United States Departments of Electrical and Computer Engineering University of Maryland College ParkMD20742 United States Institute for Theoretical Studies ETH Zürich CH 8001 Switzerland Duke Quantum Center Department of Physics Duke University DurhamNC27708 United States Department of Electrical and Computer Engineering Duke University DurhamNC27708 United States Chemical Physics Program Institute for Physical Science and Technology University of Maryland College ParkMD20742 United States

A test of quantumness is a protocol where a classical user issues challenges to a quantum device to determine if it exhibits non-classical behavior, under certain cryptographic assumptions. Recent attempts to implement such tests on current quantum computers rely on either interactive challenges with efficient verification, or non-interactive challenges with inefficient (exponential time) verification. In this paper, we execute an efficient non-interactive test of quantumness on an ion-trap quantum computer. Our results significantly exceed the bound for a classical device’s success. Copyright © 2022, The Authors. All rights reserved.

关键词： Qubits

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Assessing robustness to noise: Low-cost head ct triage

arXiv

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arXiv 2020年

作者： Hooper, Sarah M. Dunnmon, Jared A. Lungren, Matthew P. Gambhir, Sanjiv Sam Ré, Christopher Wang, Adam S. Patel, Bhavik N. Department of Electrical Engineering Department of Computer Science Department of Radiology Molecular Imaging Program Stanford Stanford University StanfordCA94305 United States

Automated medical image classification with convolutional neural networks (CNNs) has great potential to impact healthcare, particularly in resource-constrained healthcare systems where fewer trained radiologists are available. However, little is known about how well a trained CNN can perform on images with the increased noise levels, different acquisition protocols, or additional artifacts that may arise when using low-cost scanners, which can be underrepresented in datasets collected from well-funded hospitals. In this work, we investigate how a model trained to triage head computed tomography (CT) scans performs on images acquired with reduced x-ray tube current, fewer projections per gantry rotation, and limited angle scans. These changes can reduce the cost of the scanner and demands on electrical power but come at the expense of increased image noise and artifacts. We first develop a model to triage head CTs and report an area under the receiver operating characteristic curve (AUROC) of 0.77. We then show that the trained model is robust to reduced tube current and fewer projections, with the AUROC dropping only 0.65% for images acquired with a 16x reduction in tube current and 0.22% for images acquired with 8x fewer projections. Finally, for significantly degraded images acquired by a limited angle scan, we show that a model trained specifically to classify such images can overcome the technological limitations to reconstruction and maintain an AUROC within 0.09% of the original model. Copyright © 2020, The Authors. All rights reserved.

关键词： Scanning

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Development of a Selective Wet-Chemical Etchant for 3D Structuring of Silicon via Nonlinear Laser Lithography

arXiv

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arXiv 2023年

作者： Borra, Mona Zolfaghari Radfar, Behrad Nasser, Hisham Çolakoğlu, Tahir Tokel, Onur Turnalı, Ahmet Demirtaş, Merve Ustunel, Hande Toffoli, Daniele Ömer İlday, F. Turan, Raşit Pavlov, Ihor Bek, Alpan ODTÜ-GÜNAM Middle East Technical University Ankara06800 Turkey Ankara06800 Turkey Department of Electronics and Nanoengineering Aalto University Tietotie 3 EspooFI-02150 Finland Department of Physics Engineering Ankara University Ankara06100 Turkey Department of Physics Bilkent University Ankara06800 Turkey UNAM National Nanotechnology Research Center Institute of Materials Science and Nanotechnology Bilkent University Ankara06800 Turkey Department of Electrical and Electronics Engineering Bilkent University Ankara06800 Turkey Department of Electrical and Computer Engineering Boston University 8 Saint Mary’s Street BostonMA02215 United States Ankara06800 Turkey Network Technologies Department TUBITAK ULAKBIM Ankara06800 Turkey Department of Chemical and Pharmaceutical Sciences Trieste University Trieste Italy IOM-CNR Istituto Officina dei Materiali Trieste34149 Italy Micro and Nanotechnology Graduate Program of Natural and Applied Sciences Middle East Technical Turkey

Recently-demonstrated high-quality three-dimensional (3D) subsurface laser processing inside crystalline silicon (c-Si) wafers opens a door to a wide range of novel applications in multidisciplinary research areas. Using this technique, a novel maskless micro-pillars with precise control on the surface reflection and coverage are successfully fabricated by etching the laser processed region of c-Si wafer. To achieve this, a particular selective wet chemical etching is developed to follow subsurface laser processing of c-Si to reveal the desired 3D structures with smooth surfaces. Here, we report the development of a novel chromium-free chemical etching recipe based on copper nitrate, which yields substantially smooth surfaces at high etch rate and selectivity on the both laser-processed Si surface and subsurface, i.e., without significant etching of the unmodified Si. Our results show that the etch rate and surface morphology are interrelated and strongly influenced by the composition of the adopted etching solution. After an extensive compositional study performed at room temperature, we identify an etchant with a selectivity of over 1600 times for laser-modified Si with respect to unmodified Si. We also support our findings using density functional theory calculations of HF and Cu adsorption energies, indicating significant diversity on the c-Si and laser-modified surfaces. Copyright © 2023, The Authors. All rights reserved.

关键词： Morphology

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Deep convolutional neural network model for short-term electricity price forecasting

arXiv

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arXiv 2020年

作者： Cheng, Hsu-Yung Kuo, Ping-Huan Shen, Yamin Huang, Chiou-Jye Department of Computer Science and Information Engineering National Central University Computer and Intelligent Robot Program for Bachelor Degree National Pingtung University School of Electrical Engineering and Automation Jiangxi University of Science and Technology

In the modern power market, electricity trading is an extremely competitive industry. More accurate price forecast is crucial to help electricity producers and traders make better decisions. In this paper, a novel method of convolutional neural network (CNN) is proposed to rapidly provide hourly forecasting in the energy market. To improve prediction accuracy, we divide the annual electricity price data into four categories by seasons and conduct training and forecasting for each category respectively. By comparing the proposed method with other existing methods, we find that the proposed model has achieved outstanding results, the mean absolute percentage error (MAPE) and root mean square error (RMSE) for each category are about 5.5% and 3, respectively. Copyright © 2020, The Authors. All rights reserved.

关键词： Power markets

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Label-free correlative morpho-chemical tomography of 3D kidney mesangial cells

arXiv

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arXiv 2024年

作者： Butola, Ankit Ghosh, Biswajoy Park, Jaena Kwon, Minsung De la Cadena, Alejandro Mukherjee, Sudipta S. Bhargava, Rohit Boppart, Stephen A. Agarwal, Krishna Department of Physics and Technology UiT The Arctic University of Norway Tromsø9037 Norway University of Illinois Urbana-Champaign 405 N. Mathews Ave. UrbanaIL61801 United States Beckman Institute for Advanced Science and Technology University of Illinois Urbana-Champaign 405 N Mathews Avenue UrbanaIL61801 United States Department of Bioengineering University of Illinois Urbana-Champaign 1406 W Green Street UrbanaIL61801 United States Department of Chemical and Biomolecular Engineering University of Illinois Urbana-Champaign UrbanaIL United States Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign UrbanaIL United States Cancer Center at Illinois University of Illinois Urbana-Champaign UrbanaIL United States Carle Illinois College of Medicine University of Illinois Urbana-Champaign 506 S Mathews Avenue UrbanaIL61801 United States

Label-free characterization of biological specimens seeks to supplement existing imaging techniques and avoid the need for contrast agents that can disturb the native state of living samples. Conventional label-free optical imaging techniques are compatible with living samples but face challenges such as poor sectioning capability, fragmentary morphology, and lack chemical specific information. Here, we combined simultaneous label-free autofluorescence multi-harmonic (SLAM) microscopy and gradient light interference microscopy (GLIM) to extract both chemical specific and morphological tomography of 3D cultured kidney mesangial cells. Imaging 3D in vitro kidney models is essential to understand kidney function and pathology. Our correlative approach enables imaging and quantification of these cells to extract both morphology and chemical-specific signals that is crucial for understanding kidney function. In our approach, SLAM offers a nonlinear imaging platform with a single-excitation source to simultaneously acquire autofluorescence (FAD and NAD(P)H), second, and third harmonic signal from the 3D cultured cells. Complementarily, GLIM acquires high-contrast quantitative phase information to quantify structural changes in samples with thickness of up to 250 µm. Our correlative imaging results demonstrate a versatile and hassle-free platform for morpho-chemical cellular tomography to investigate functions such as metabolism and matrix deposition of kidney mesangial cells in 3D under controlled physiological conditions. Copyright © 2024, The Authors. All rights reserved.

关键词： Cell culture

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Longitudinal and Geographic Trends in Perceived Racial Discrimination Among Adolescents in the United States: The Adolescent Brain Cognitive Development Study

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Journal of Adolescent Health 2025年第1期77卷 118-127页

作者： Fields, Christopher T. Black, Carmen Calhoun, Amanda J. Rosenblatt, Matthew Rodriguez, Raimundo Aina, Joseph Thind, Jannat K. Grayson, Jalen Khalifa, Fahmi Assari, Shervin Zhou, Xin Nagata, Jason Gee, Dylan G. Program for Recovery and Community Health Department of Psychiatry Yale School of Medicine New Haven Connecticut United States Department of Radiology Magnetic Resonance Research Center Yale School of Medicine New Haven Connecticut United States Institute of Living at Hartford Healthcare Hartford Connecticut United States Department of Psychiatry Yale School of Medicine New Haven Connecticut United States Department of Psychiatry University of Connecticut Health Center Farmington Connecticut United States Department of Electrical and Computer Engineering Morgan State University Detroit MI United States Semel Institute for Neuroscience and Human Behavior University of California-Los Angeles Los Angeles California United States Department of Family Medicine Charles R Drew University of Medicine and Science Los Angeles California United States Department of Biostatistics Yale School of Medicine New Haven Connecticut United States Division of Adolescent and Young Adult Medicine Department of Pediatrics University of California San Francisco San Francisco California United States Department of Psychology Yale University New Haven Connecticut United States

Purpose: To assess longitudinal and geographic variation in perceived discrimination from ages 10–11 to 13–14 years in the Adolescent Brain Cognitive Development cohort, and to examine how these experiences are shaped by contextual factors such as neighborhood segregation and state-level racial bias. Methods: Data were drawn from the longitudinal Adolescent Brain Cognitive Development Study (release 5.1), analyzing years 1, 2, and 4, corresponding to approximate ages 10–11, 11–12, and 13–14 years. Perceived discrimination was assessed using items adapted from the Perceived Discrimination Scale. Mixed-effects logistic regression models examined how perceived discrimination varied across time, demographic factors, and contextual variables, with models weighted using American Community Survey raked propensity scores to ensure national representativeness. Results: Black, Asian American and Pacific Islander, and Other/Multiracial non-Hispanic youth showed increasing trajectories of perceived discrimination over time, while Native American and White non-Hispanic youth exhibited decreasing trends. Significant geographic variation emerged, with Black youth reporting elevated discrimination across all regions, particularly in the West and South. Youth living in areas with concentrated poor Black households and in states with high anti-Black bias reported higher discrimination. Youth with immigrant backgrounds generally reported higher levels of perceived discrimination across most racial/ethnic groups. Discussion: Perceived discrimination follows distinct developmental trajectories during early adolescence that vary significantly by race, ethnicity, geography, and structural context. These findings highlight the critical need for targeted interventions during this developmental period, particularly for Black, Asian American and Pacific Islander, and Other/Multiracial youth. Context-specific approaches to addressing racism are essential for mitigating its harmful effects on a

关键词： Adolescent health Health disparities Intergroup relations Interpersonal racism Public health Racial discrimination Racism Racism-related stress Social determinants of health

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